Comparer des méthodes

	Régression spatio-temporelle spatiale	Krigage spatio-temporel
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	1990s–2000s	1999
Auteur d'origine	Anselin, LeSage, Pace and colleagues in spatial econometrics	Cressie & Huang; Kyriakidis & Journel
Type	Spatio-temporal regression model	Geostatistical interpolation
Source fondatrice	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Cressie, N., & Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1340.
Alias	spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression	spatiotemporal kriging, ST-kriging, space-time geostatistical interpolation, kriging in space-time
Apparentées	6	4
Résumé	Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data.	Space-Time Kriging is a geostatistical interpolation method that predicts an unknown variable at any location and time by borrowing strength from nearby observations in both space and time simultaneously. It models the joint spatial-temporal covariance structure through a space-time variogram, then uses optimal linear weights to produce predictions with quantified uncertainty.